Keywords
Single nucleotide polymorphism
Epigenetics
Noncommunicable diseases
Gene expression
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Abstract
Objective: To select and systematically analyze papers in which the evaluation of the correlation between polymorphisms and anthropometric and biochemical measurements were discussed. Methods: This is an integrative review, based on the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and using the PubMed database with SNPs, being possible to insert a SNP of interest in the search field and have access only to publications referring to that specific genetic marker, the period of the researched papers was from 2017 to 2021. Results: Based on the search strategy, 96 papers were identified on the PubMed platform, it was found that some genetic alterations (base change) can influence the development of phenotypes associated with diseases such as diabetes and obesity, among the papers analyzed, an example was the SNPs rs7901695 and rs12255372 in the TCF7L2 gene with the transcript found for glucose regulation, resulting in a susceptibility for DM2. Final considerations: Epigenetic factors may act influencing the phenotype along with genetic factors, furthermore, one should consider genetic heterogeneity and difference among populations when investigating the association of polymorphisms and gene expression associated with non-communicable diseases.
References
ADAMSKA EP, et al. Metabolomics Reveal Altered Postprandial Lipid Metabolism After a High-Carbohydrate Meal in Men at High Genetic Risk of Diabetes. The Journal of Nutrition: National Library of Medicine. 2019; 149: 915 - 922.
BEGO T, et al. Association of FTO gene variant (rs8050136) with type 2 diabetes and markers of obesity, glycaemic control and inflammation. Journal of medical biochemistry. 2019; 38(2): 153–163.
BOUTARI C e MANTZOROS CS. A 2022 update on the epidemiology of obesity and a call to action: as its twin COVID-19 pandemic appears to be receding, the obesity and dysmetabolism pandemic continues to rage on. Metabolism. 2022; 133: 155217.
CHEN B, et al. Association of fat mass and obesity-associated and retinitis pigmentosa guanosine triphosphatase (GTPase) regulator-interacting protein-1 like polymorphisms with body mass index in Chinese women. Endocrine jornal. 2018: 65(7): 783–791.
DAGHESTANI M, et al. ADRB3 polymorphism rs4994 (Trp64Arg) associates significantly with bodyweight elevation and dyslipidaemias in Saudis but not rs1801253 (Arg389Gly) polymorphism in ARDB1. Lipids in health and disease. 2018; 17(1).
DUICU C, et al. FTO rs 9939609 SNP Is Associated With Adiponectin and Leptin Levels and the Risk of Obesity in a Cohort of Romanian Children Population. Medicine (Baltimore). 2016; 95.
GALVÃO TF, et al. Principais itens para relatar Revisões sistemáticas e Meta-análises: A recomendação PRISMA. Epidemiol. Serv. Saúde. 2015; 24.
O´BEIRNE SL, et al. Type 2 Diabetes Risk Allele Loci in the Qatari Population. PLoS One. 2016; 11.
GU Z. et al. FTO polymorphisms are associated with metabolic dysfunction-associated fatty liver disease (MAFLD) susceptibility in the older Chinese Han population. Clinical interventions in aging. 2020; 15: 1333–1341.
KHAN SM, et al. Association between type 2 diabetes mellitus & TCF7L2 gene variants in the Emirati population: Genetics of diabetes in the United Arab Emirates. National Library of Medicine: American Journal of Human Biology. 2020; 33.
HOSSEINI FE, et al. Dietary patterns modify the association between fat mass and obesity-associated genetic variants and changes in obesity phenotypes. The British journal of nutrition. 2019; 121(11): 1247–1254.
KOOCHAKPOUR G, et al. Evaluating the interaction of common FTO genetic variants, added sugar, and trans-fatty acid intakes in altering obesity phenotypes. Nutrition, metabolism, and cardiovascular diseases: NMCD. 2019; 29(5): 474–480.
LÓPEZ GR, et al. Common polymorphisms in MC4R and FTO genes are associated with BMI and metabolic indicators in Mexican children: Differences by sex and genetic ancestry. Gene. 2020; 754: 144840.
PRADEEPA R e MOHAN V. Epidemiology of type 2 diabetes in India. Indian Journal of Ophthalmology. 2021; 69.
RANASINGHE P, et al. The range of non-traditional anthropometric parameters to define obesity and obesity-related disease in children: a systematic review. European journal of clinical nutrition. 2020; 373–384.
RANA S e BHATTI AA. Predicting anthropometric and metabolic traits with a genetic risk score for obesity in a sample of Pakistanis. Sci Rep. 2021; 11.
REDDY A, et al. Intron-specific single nucleotide polymorphisms of Fat mass and obesity- associated gene in obese and overweight individuals of the Indian adult population- A pilot study. Current diabetes reviews. 2019; 16(1): 84–94.
REDONDO MJ, et al. TCF7L2 Genetic Variants Contribute to Phenotypic Heterogeneity of Type 1 Diabetes. National Library of Medicine. 2018; 41: 311-317.
SAKAMOTO Y, et al. Beta-3-adrenergic receptor rs4994 polymorphism is a potential biomarker for the development of nonalcoholic fatty liver disease in overweight/obese individuals. Disease markers. 2019; 4065327.
SAKLAYEN MG. The Global Epidemic of the Metabolic Syndrome. Curr Hypertens Rep, 2018; 20.
SALINAS SMA, et al. Assessment of biochemical parameters and characterization of TNFα -308G/A and PTPN22 +1858C/T gene polymorphisms in the risk of obesity in adolescents. Biomedical Reports. 2015; 107-111.
SEDAGHATI KB, et al. Lack of association between FTO gene variations and metabolic healthy obese (MHO) phenotype: Tehran Cardio-metabolic Genetic Study (TCGS). Eating and weight disorders. 2018; 25(1): 25-35.
SINGH S, et al. Clinical Prediction of Type 2 Diabetes Mellitus (T2DM) via Anthropometric and Biochemical Variations in Prakriti. Diseases. 2022; 10.
TARNOWSKI M, et al. Effect of FTO and IGF2BP2 gene polymorphisms on duration of pregnancy and Apgar scores in women with gestational diabetes. Journal of obstetrics and gynaecology: the journal of the Institute of Obstetrics and Gynaecology. 2019; 39(2): 151–156.
VALADARES LTS, et al. Prevalence of metabolic syndrome in Brazilian adults in the last 10 years: a systematic review and meta-analysis. BMC Public Health. 2022; 22.
WANG K, et al. A genome-wide association study on obesity and obesity-related traits. PLoS One. 2011; 6.
ZAFAR U. et al. Adrenergic receptor beta-3 rs4994 (T>C) and liver X receptor alpha rs12221497 (G>A) polymorphism in Pakistanis with metabolic syndrome. The Chinese journal of physiology. 2019; 62(5): 196–202.
ZAHARAN NL, et al. Non-synonymous single-nucleotide polymorphisms and physical activity interactions on adiposity parameters in Malaysian adolescents. Frontiers in endocrinology. 2018; 9: 00209.
ZHAO F, et al. The Uyghur population and genetic susceptibility to type 2 diabetes: potential role for variants in CAPN10, APM1 and FUT6 genes. Journal of Cellular and Molecular Medicine. 2016; 20: 2138-2147.